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NTIS 바로가기식품과학과 산업 = Food science and industry, v.50 no.4, 2017년, pp.50 - 64
이수진 (서울여자대학교 식품공학과) , 노봉수 (서울여자대학교 식품공학과)
Applications of the second generation of electronic nose in various field such as new food product development, slight rancidity during induction period, classification of similar products, discovery of odor, and odor reduction were reviewed. The possibilities of using electronic noses in areas that...
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핵심어 | 질문 | 논문에서 추출한 답변 |
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주관적인 방법인 관능검사의 한계는 무엇인가? | 휘발성분을 측정방법으로는 주관적인 방법인 관능검사법과 객관적인 방법인 기계적 분석법으로 크게 나누어 볼 수 있다. 주관적인 방법인 관능검사의 경우 여러 장점에도 불구하고 식중독의 위험이 뒤따르거나 부패된 식품 또는 변질 가능성이 우려되는 식품에서 이취 성분은 관능검사 요원마저도 꺼리는 어려운 점이 있다. 혹여 이취성 분이 매우 적은 양이라 불쾌감을 조성하지는 않는다 하더라도 유해물질일 가능성이 높다고 판단되면 인체를 대상으로 확인 작업에 참여하는 일은 위험을 초래할 수도 있기 때문이다. | |
휘발성분 측정방법에는 어떤 것이 있는가? | 식품제조 공정과 유통 저장조건에서 여러 가지의 휘발성분이 생성되므로 이들을 분석하고 관리하는 일은 중요하다. 휘발성분을 측정방법으로는 주관적인 방법인 관능검사법과 객관적인 방법인 기계적 분석법으로 크게 나누어 볼 수 있다. 주관적인 방법인 관능검사의 경우 여러 장점에도 불구하고 식중독의 위험이 뒤따르거나 부패된 식품 또는 변질 가능성이 우려되는 식품에서 이취 성분은 관능검사 요원마저도 꺼리는 어려운 점이 있다. | |
객관적인 분석 방법의 장점은 무엇인가? | 객관적인 분석 방법인 gas chromatography-mass spectrometry (GC-MS)와 같은 분석방법이 이러한 문제를 부분적으로 대신해 줄 수는 있을 것이다 (1,2). 분석기기 장비를 사용하면 불쾌한 성분이나 유해물질을 밝힐 수 있다는 점 외에도 이들의 종류와 농도까지도 밝힐 수 있으며 많은 시료에 대하여도 높은 재현성을 제공할 수가 있다. 그러나 원하는 성분이외의 다른 물질들을 분리시켜야 하는 전처리 작업이 필요하며 성분의 특징에 따라 그에 합당한 칼럼을 선택해야 하고 또 적절한 분리조건 등을 확립해야 한다. |
Hodgkin D. Simmonds D. Sensory technology for flavor analysis. Cereal Foods World 40: 186-191 (1995)
Chou UD. Use and development of sensation sensor. Bulletin Food Technol. 8: 122-131 (1995)
Fisk ID. Kettle A. Hofmeister S. Virdie A. Kenny JS. Discrimination of roast and ground coffee aroma. Flavour 1: 14 (2012)
Shilbayeh NF. Iskandarani MZ. Quality control of coffee using an electronic nose system. Am. J. Appl. Sci. 1: 129-135 (2004)
Michishita T. Akiyama M. Hirano Y. Ikeda M. Sagara Y. Araki T. Gas chromatography/olfactometry and electronic nose analyses of retronasal aroma of espresso and correlation with sensory evaluation by an artificial neural network. J. Food Sci. 75: S477-S489 (2010)
Baldwin EA. Bai J. Plotto A. Dea S. Electronic noses and tongues: Applications for the food and pharmaceutical industries. Sensors 11: 4744-4766 (2011)
Vietoris V. Zajac P. Capla J. MendelovaA. KrizanovaK. BenesovaL. Comparison of coffee species by sensory panel and electronic nose. J. Microbio. Biotech. Food Sci. 5: 234-237 (2015)
Fu J. Li G. Qin Y. Freeman WJ. A pattern recognition method for electronic noses based on an olfactory neural network. Sensor Actuat. B: Chem. 125: 489-497 (2007)
Fu J. Huang C. Xing J. Zheng J. Pattern classification using an olfactory model with PCA feature selection in electronic noses: Study and Application. Sensors. 12: 2818-2830 (2012)
Kim SR. Flavor analysis of foods by electronic nose. Food Sci. Ind. 30: 126-133 (1997)
Noh BS. Analysis of volatile compounds using electronic nose and its application in food industry. Korean J. Food Sci. Technol. 37: 1048-1064 (2005)
Stetter JR. Findlay MW. Schroeder KM. Yue C. Penrose WR. Quality classification of grain using a sensor array and pattern recognition, Anal. Chim. Acta 284: 1-11 (1993)
Bartlett PN. Elliott JM. Gardner JW. Electronic noses and their application in the food industry. Food Technol. 51: 44-48 (1997)
Schaller E. Bosset JO. Escher F. 'Electronic Noses' and their application to food. Lebensm.-Wiss. u.-Technol. 31: 305-316 (1998)
Bourrounet B. Talou T. Gaset A. Application of a multigas sensor device in the meat industry for boar-taint detection. Sensor Actuat. B 26-27: 250-254 (1995)
Capelli L. Sironi S. Rosso RD. Electronic noses for environmental monitoring applications. Sensors 14: 19979-20007 (2014)
Baby RE. Cabezas M. de Reca ENW. Electronic nose: a useful tool for monitoring environmental contamination. Sensor Actuat. B: Chemical 69: 214-218 (2000)
Tang K-T. Chiu S-W. Pan C-H. Hsieh H-Y. Liang Y-S. Liu S-C. Development of a portable electronic nose system for the detection and classification of fruity odors. Sensors 10: 9179-9193 (2010)
Kiani S. Minaei S.Ghasemi-Varnamkhasti M. Application of electronic nose systems for assessing quality of medicinal and aromatic plant products: A review. J. Appl. Res. Medicinal Aromatic Plants 3: 1-9 (2016)
Byun H-G. Yu JB. Huh JS. Lim J-O. Exhaled breath analysis system based on electronic nose techniques applicable to lung diseases. Hanyang Med. Rev. 34: 125-129 (2014)
Montuschi P. Mores N. TroveA. Mondino C. Barnes PJ. The Electronic nose in respiratory medicine. Respiration 85: 72-84 (2013)
https://en.wikipedia.org/wiki/Electronic_nose
Askim JR. Morteza M. Suslick KS. Optical sensor arrays for chemical sensing: the optoelectronic nose. Chem. Soc. Rev. 42: 8649-8682 (2013)
Musto CJ. Lim SH. Suslick KS. Colorimetric detection and identification of natural and artificial sweeteners. Anal. Chem. 81: 6526-6533 (2009)
Feng L. Musto CJ. Kemling JW. Lim SH. Suslick KS. : A colorimetric sensor array for identification of toxic gases below permissible exposure limits. Chem. Commun. 46: 2037-2039 (2010)
Ahn M-W. Park K-S. Heo J-H. Park J-G. Kim D-W. Choi K. Lee J-H. Hong S-H. Gas sensing properties of defect-controlled ZnOnanowire gas sensor. Appl. Phys. Lett. 93: 263103-1-263103-3 (2008)
Lee JK. Design and implementation of multi-gas recognition algorithm for low power driving with wireless electronic nose. MS thesis, Kyungil University (2016)
Hong HK. Kwon CH. Yun DH. Kim S-R. Lee K. Kim IS. Sung YK. Fabrication and characterization of portable electronic nose system for identification of CO/HC gases. J, Sen. Sci. Technol. 6: 47-53 (1997)
Choi IH. The study on the fabrication and sensing characteristics of semiconductor gas sensor array for the electronic nose system. MS thesis, Dae Jeon University (2006)
Lee KC. A study on SnO2 thin film gas sensor arrays for the electronic nose system. MS thesis, Chonnam National University (2001)
Hwang YW. Moon J-Y. Baek S-R. Analysis of the relationship between odor sensor and the air dilution olfactory method in industrial complex odor. J. Korean Soc. Odor Res. Eng. 11: 209-218 (2004)
Dong H. Kim KH. Han K-Y. Choi JY. Noh BS. Effect of various light emitting diode irradiation on volatile profiles of perilla oil using mass spectrometry-based electronic nose. Food Sci. Biotechnol. 24: 481-487 (2015)
https://www.google.co.kr/search?sourcehp&ei3R5DWuv3IMzz8QX0zauACg&q%28electronic+nose%29+and+%28review+paper%29+and%28food%29&oq%28electronic+nose%29+and+%28review+paper%29+and%28food%29&gs_lpsy-ab.3...5571.39497.0.39775.71.54.10.0.0.0.2434.8374.6j35j3j9-1.45.0....0...1c.1.64.psy-ab..17.36.6479.0..0j0i30k1j0i19k1j0i30i19k1j0i13i30k1j0i13i10i30k1j0i10i30k1j0i13i30i19k1j0i8i13i30k1j33i160k1j33i21k1.0.lf4Peh0We_A
Noh BS. Quality assessment and flavor analysis of Jeju beer for new product development. Final report of Jeju Industry-leading Broadband Economies Supporters, April, 30th (2012)
Mohapatra P. Cox N. Banerjee P. Development of flavor profile of pet food palatants using electronic nose and electronic tongue. 16th International Symposium on Olfaction and Electronic Nose, Abstract #31, June 28th-July 1st, Exhibition and Convention Centre, Dijon, France (2015)
Cheli F. Bonetempo V. Dell'Orto V. E-nose and E-tongue: an analytical tool for quality control and management in the pet food industry. Sens. Transducers 213: 24-29 (2017)
Shen N. Moizuddin S. Wilson L. Duvick S. White P. Pollak L. Relationship of electronic nose analyses and sensory evaluation of vegetable oils during storage. J. Am. Oil Chem. Soc. 78: 937-940 (2001)
Kim KH. Hong EJ. Park SJ. Kang JW. Noh BS. Pattern recognition analysis for volatile compounds of the whole, skim, UHT-, HTST-, and LTLT- milk under LED irradiations. Korean J. Food Sci Ani. Resour. 31: 595-602 (2011)
Olafsdottir G. Nesvadba P. Natale CD. Careche M. Oehlenschlager J. Tryggvadottir SV. Schubring R. Kroeger M. Heia K. Esaiassen M. Macagnano A. Jorgensen BM. Multisensor for fish quality determination. Trends Food Sci. Technol. 15: 86-93 (2004)
Olafsdottir G. Kristbergsson K. Electronic-nose technology : Application for quality evaluation in the fish industry. In Odors in the food industry. Nicolay X. (ed), pp.57-74, ISBN-13: 978-0387335100 Springer, Springer International Publishing AG. Dordrecht, Netherland (2006)
Olafsdottir G. Martinsdottir E. Jonsson EH. Rapid gas sensor measurements to determine spoilage of capelin (Mallotus villosus). J. Agric. Food Chem. 45: 2654-2659 (1997)
Barbri NE. Amari A. Vinaixa M. Bouchikhi B. Correig X. Llobet E. Building of a metal oxide gas sensor-based electronic nose to assess the freshness of sardines under cold storage. Sensor Actuat. B. 128: 235-244 (2007)
Barbri NE. Llobet E. Bari NE. Correig X. Bouchikhi B. Application of a portable electronic nose system to assess the freshness of Moroccan sardines. Materi. Sci. Eng. C 28: 666-670(2008)
Gibson TD. Prosser O. Hulbert JN. Marshall RW. Corcoran P. Lowery P. Ruck-Keene EA. Heron S. Detection and simultaneous identification of microorganisms from headspace samples using an electronic nose, Sensor Actuat. B 44: 413-422 (1997)
Tian X-Y. Cai Q. and Zhang YM. Rapid classification of hairtail fish and pork freshness using an electronic nose based on the PCA method. Sensors 12: 260-277 (2012)
Zou Y. Wan H. Zhang X. Ha D. Wang P. Electronic nose and electronic tongue. In Bioinspired Smell and Taste Sensors. Wang P. Liu Q. Wu C. Hsia KJ. (eds), pp 19-44, Springer International Publishing AG. Dordrecht, Netherlands (2015)
Wilson AD. Diverse applications of electronic-nose technologies in agriculture and forestry. Sensors 13: 2295-2348 (2013)
Vallone S. Lloyd NW. Ebeler SE. Zakharov F. Fruit volatile analysis using an electronic nose. J. Vis. Exp. 61 : e3821, doi:10.3791/3821 (2012)
Heinemann CLPH. Irudayaraj J. Detection of apple deterioration using an electronic nose and zNose. Trans. Am. Soc. Agri. Biol. Eng. 50: 1417-1425 (2007)
Corrado DN. Manuela Z-S. Antonella M. Roberto P. Bernd H. Arnaldo D'A. Outer product analysis of electronic nose and visible spectra: application to the measurement of peach fruit characteristics. Anal. Chim. Acta 459: 107-117 (2002)
Defilippi BG. Juan WS. Valdes H. Moya-Leon MA. Infante R. Campos-Vargas, R. The aroma development during storage of Castlebrite apricots as evaluated by gas chromatography, electronic nose, and sensory analysis. Postharvest Biol Tech. 51: 212-219 (2009)
Gu X. Sun Y. Tu K. Dong Q. Pan L. Predicting the growth situation of Pseudomonas aeruginosa on agar plates and meat stuffs using gas sensors. Scientific Reports 6: 38721 (2016)
Papadopoulou OS. Panagou EZ. Mohareb FR. Nychas GE. Sensory and microbiological quality assessment of beef fillets using a portable electronic nose in tandem with support vector machine analysis. Food Res. Int. 50: 241-249 (2013)
Hong XZ. Wang J. Hai Z. Discrimination and prediction of multiple beef freshness indexes based on electronic nose. Sensor Actuat. B: Chem. 161: 381-389 (2012)
Berna A. Metal oxide sensors for electronic noses and their application to food analysis. Sensors 10: 3882-3910 (2010)
Vinaixa M. Vergara A. Duran C. Llobet E. Badia C. Fast detection of rancidity in potato crisps using e-noses based on mass spectrometry or gas sensors. Sensor Actuat. B 106: 67-75 (2005)
Kaushal A. Gupta P. Electronic nose evolution for food adulteration: A Review. International J. Eng. Develop. Res. 5: 108-112 (2017)
Peris M. Escuder-Gilabert L. A 21st century technique for food control: Electronic noses. Anal. Chim. Acta 638: 1-15 (2009)
OAlafsdottir G. Hognadottir AA. Martinsdottir E. Jonsdottir H. Application of an electronic nose to predict total volatile bases in Capelin (Mallotus villosus) for fishmeal production. J. Agric. Food Chem. 48: 2353-2359 (2000)
Ramamoorthy HV. Mohamed SN. Devi DS. E-Nose and E-Tongue: Applications and advances in sensor technology. J. NanoSci. Nano-Tech. 2: 370-376 (2014)
Noh BS. Oh SY. Kim SJ. Pattern analysis of volatile components for domestic and imported Angelica gigas Nakai using GC based on SAW sensor. Korean J. Food Sci. Technol. 35: 144-148 (2003)
Oh SY. Noh BS. Pattern analysis of volatile components for domestic and imported Cnidium officinale using GC based on SAW sensor. Korean J. Food Sci. Technol. 35: 994-997 (2003)
Cho YS. Noh BS. Quality evaluation of dried Laver (Porphyrayezoensis Ueda) using electronic nose based on metal oxide sensor or GC with SAW sensor during storage. Korean J. Food Sci. Technol. 34: 947-953 (2002)
Gan HL. Man YBC. Tan CP. NorAini I. Nazimah SAH. Characterisation of vegetable oils by surface acoustic wave sensing electronic nose. Food Chem. 89: 507-518 (2005)
Marina AM. Man YBC. Amin I. Use of the SAW sensor electronic nose for detecting the adulteration of virgin coconut oil with RBD palm kernel olein. J. Am. Oil Chem. Soc. 87: 263-270 (2010)
Suh HS. Kang HJ. Chung EH. Hwang IK. Application of GCSAW(Surface Acoustic Wave) electronic nose to classification of origins and blended commercial brands in roasted ground coffee beans. Korean J. Food Cookery Sci. 22: 299-306 (2006)
https://www.alpha-mos.com/documentation
Wisniewska P. Sliwinska M. Dymerski T. Wardencki W. Namiesnik J. Comparison of an electronic nose based on ultrafast gas chromatography, comprehensive two-dimensional gas chromatography, and sensory evaluation for an analysis of type of whisky. J. Chem. 2017: Article ID 2710104, 13 pages (2017)
Park EY. Kim JH. Noh BS. Application of the electronic nose and artificial neural network system to quality of the stored soymilk. Food Sci. Biotechnol. 11: 20-323 (2002a)
Park EY. Noh BS. Ko SH. Prediction of shelf life for soybean curd by the electronic nose and artificial neural network system. Food Sci. Biotechnol. 11: 245-251 (2002b)
Kim MJ. Park J-H. Electric-nose/tongue and their applications. Food Ind. Nutri. 21: 15-18 (2016)
Flambeau KJ. Lee W-J, Yoon J. Discrimination and geographical origin prediction of washed specialty Bourbon coffee from different coffee growing areas in Rwanda by using electronic nose and electronic tongue. Food Sci. Biotech. 26: 1245-1254 (2017)
Korel F. Luzuriaga DA. Balaban MO. Objective quality assessment of raw tilapia (Oreochromis niloticus) fillets using electronic nose and machine vision. J Food Sci. 66: 1018-1024 (2001)
Haddi Z. Alami H. Bari NE. Tounsi M. Barhoumi H. Maaref A. Jaffrezic-Renault N. Bouchikhi B. Electronic nose and tongue combination for improved classification of Moroccan virgin olive oil profiles. Food Res. Int. 54: 1488-1498 (2013)
Apetrei C. Apetrei IM. Villanueva S. de Saja J.A. Gutierrez-Rosales Rodriguez-Mendez FML. Combination of an e-nose, an e-tongue and an e-eye for the characterisation of olive oils with different degree of bitterness. Anal. Chim. Acta 663: 91-97 (2010)
Longobardi F. Casiello G. Ventrella A. Mazzilli V. Nardelli A. Sacco D. Catucci L. Agostiano A. Electronic nose and isotope ratio mass spectrometry in combination with chemometrics for the characterization of the geographical origin of Italian sweet cherries. Food Chem. 170: 90-96 (2015)
Banerjee R. Modak A. Mondal S. Tudu B. Bandyopadhyay R. Bhattacharyya N. Fusion of electronic nose and tongue response using fuzzy based approach for black tea classification. Procedia Technol. 10: 615-622 (2013)
Rosa ARD. Leone F. Cheli F. Chiofalo V. Fusion of electronic nose, electronic tongue and computer vision for animal source food authentication and quality assessment : A review. J. Food Eng. 210: 62-75 (2017)
Gil-Sanchez L. Sotoa J. Martinez-Manez R. Garcia-Breijoa E. Ibanez J. Llobet E. A novel humid electronic nose combined with an electronic tongue for assessing deterioration of wine. Sensor Actuat. A 171: 152-158 (2011)
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